Presence Analytics: Discovering Meaningful Patterns about Human Presence Using WLAN Digital Imprints

M. H. S. Eldaw, M. Levene, George Roussos
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引用次数: 6

Abstract

In this paper we illustrates how aggregated WLAN activity traces provide anonymous information that reveals invaluable insight into human presence within a university campus. We show how technologies supporting pervasive services, such as WLAN, which have the potential to generate vast amounts of detailed information, provide an invaluable opportunity to understand the presence and movement of people within such an environment. We demonstrate how these aggregated mobile network traces offer the opportunity for human presence analytics in several dimensions: social, spatial, temporal and semantic dimensions. These analytics have real potential to support human mobility studies such as the optimisation of space use strategies. The analytics presented in this paper are based on recent WLAN traces collected at Birkbeck College of University of London, one of the participants in the Eduroam network.
存在分析:利用WLAN数字印记发现人类存在的有意义模式
在本文中,我们说明了聚合的WLAN活动跟踪如何提供匿名信息,从而揭示了对大学校园内人类存在的宝贵见解。我们展示了支持普及服务(如WLAN)的技术如何能够生成大量详细信息,从而为了解这种环境中人员的存在和活动提供了宝贵的机会。我们展示了这些聚合的移动网络痕迹如何在几个维度上为人类存在分析提供机会:社会、空间、时间和语义维度。这些分析具有支持人类流动性研究的真正潜力,例如空间使用策略的优化。本文中提出的分析是基于最近在伦敦大学伯克贝克学院收集的WLAN痕迹,该学院是Eduroam网络的参与者之一。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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